AI technologies are known for their impressive ability to comb through large amounts of data and create a synopsis highlighting the most relevant or prevalent information. Harnessing this aspect of AI allows for cybersecurity breakthroughs that are effective not only at mitigating the risk of attacks through the mainstream internet but also in dark web monitoring. With the recent addition of DarkBERT, AI is beginning to infiltrate the dark web, and when used properly this specialized language model can be the foundation of better dark web monitoring.
Dark web monitoring is an essential part of complete cybersecurity protection because the dark web can be a source of sensitive data brokering that can allow threat agents to acquire your organization’s information. Phishing and other social engineering attacks can use names or contact information from your organization to launch more targeted attacks. Dark web chatter may indicate an interest in abusing your brand.
AI is now a vital tool in combating these threats. How does AI-driven dark web monitoring work? This article will help you understand this powerful defensive asset.
Understanding Dark Web Monitoring
The dark web encompasses parts of the internet that can only be accessed using specific web browsers. Because the information stored on the dark web is not easily accessible, the dark web has a looser structure with decentralized enforcement and is often used for illegal activities. The dark web is a significant threat to organizations that choose to ignore it because both skilled and amateur threat actors can navigate this clandestine medium and acquire information that they can then abuse.
So what is dark web monitoring? Using both AI and human intelligence, raw data from across the dark web is collected and analyzed. Any information that is leaked, sensitive, or stolen from your organization is observed and reported to your cybersecurity team, which allows for quick action to mitigate the threat.
The importance of this aspect of cybersecurity cannot be overstated. Digital threats occur because hackers breach or attempt to disrupt your business. These threat actors have largely unregulated access to any information that makes it to the dark web, and without an effective dark web monitoring system, you will be vulnerable to risks such as:
Disruption of Business Operations: Dark web criminals can infiltrate and disrupt business operations, leading to halted services, depreciated organizational value, and significant revenue losses.
Reputation Damage: Successful cyberattacks can tarnish an organization’s reputation, leading to a loss of customer trust and potential long-term damage to the brand.
Fraud through Business Email Compromises: Criminals can use information from the dark web to launch sophisticated phishing attacks, leading to financial fraud or unauthorized data access.
Intellectual Property Theft: Threat actors can steal proprietary information and sell it to competitors, giving them an unfair advantage and causing potential financial and strategic losses for the victimized organization.
Ransom Attacks: Organizations can find their systems held hostage with ransomware, where criminals demand payment to restore access.
Addressing these threats only after they manifest can result in irreversible consequences. An efficient dark web monitoring system is paramount to preemptively identify and neutralize these risks.
The Emergence Of AI In Cybersecurity
Many domains of cybersecurity are actually excellent opportunities to unleash AI to advance the effectiveness of both threat detection and response. Creating environments like zero-trust architecture and blockchain has made it easier for AI to trace the flow of information; thus, if defenses are breached and data stolen, AI can quickly identify the deviation and respond. Contemporary cybersecurity solutions almost always complement human intelligence with protocols that use information sorted by AI.
Utilizing AI to comprehend and compile information that protects your digital landscape promotes dark web threat intelligence. Entire AI language models have been developed to be trained to combat cybercrime, including a recent addition, DarkBERT.
What Is DarkBERT?
DarkBERT is a specialized language model that has been trained in navigating the dark web and understands how to assess cyberthreats. With a detailed understanding of a cybercriminal’s language and interests, it can continuously scan dark web sources for specific references to an organization or other potentially harmful information.
DarkBERT distinguishes itself from other language models because its training has been almost exclusively on the dark web, so it is not bogged down with information unnecessary to its intent. Because its training focuses on the cybersecurity threats that can be found on the dark web, it knows exactly what keywords and information could result in an illicit transaction or threat. This knowledge has enabled DarkBERT to identify sites and data across the dark web that present danger to digital platforms and organizations and alert cybersecurity teams of the potential threats.
The Benefits Of AI-Enabled Dark Web Monitoring
AI-enabled dark web monitoring is the gold standard in dark web threat intelligence. AI-driven monitoring systems can accomplish more than a simple search and alert program because they learn and adapt to evolving threat language. In addition, an AI-enabled dark web monitoring platform offers:
Faster Threat Detection and Response Time
AI technologies can quickly identify potential threats on the dark web, drastically reducing the time between detection and response. While there are various metrics that gauge the effectiveness of a cybersecurity strategy, MTTR (mean time to respond/resolve) is one of the most important metrics when measuring effectiveness. AI can detect potential threats quickly and issue an automatic response, which immediately alerts the rest of the cybersecurity team. This results in the amount of time it takes to launch a full response being dramatically reduced.
Better Protection Against Evolving Cyber Threats
AI continually learns and adapts. This offers growing protection against new and evolving threats that traditional systems might miss, and only improves over time. An AI trained on dark web monitoring will also be able to adapt to the workarounds threat agents may use because it is familiar with the dark web landscape.
Automated Data Crawling
AI can automate the tedious process of crawling the vast expanses of the dark web. This reduces the chances of a threat going undetected, even if it is buried in layers of anonymity on the dark web that could be exhausting for humans or simpler monitoring programs.
How AI Is Revolutionizing Dark Web Monitoring
The advent of AI technologies has revolutionized the field of dark web monitoring. Below, we delve into some of the ways AI enhances the efficacy and techniques of monitoring the dark web:
Advanced Data Collection and Scanning Techniques
AI can sift through massive amounts of data swiftly, pinpointing vital information that enhances its own training while simultaneously alerting cybersecurity teams about potential threats. The AI’s tireless, laser-focused scanning ensures that the data it gathers is more valuable and actionable than ever before.
It categorizes the information it encounters on the dark web, sorting data into relevant tags. This enables cybersecurity teams to promptly identify threats that necessitate immediate action. Streamlining this process minimizes the window of opportunity for hackers and other malicious agents to exploit or sell sensitive information.
Detection of Illicit Activities Through Natural Language Processing (NLP)
Natural Language Processing (NLP) is a pivotal feature of AI technologies. It enhances the interpretability of the extensive data sets acquired through dark web monitoring. When the AI identifies threats or abnormal patterns within this data, it uses NLP to compare the language to that of known threat actors or concealed communications.
This mastery of language patterns allows AI to alert security teams about suspicious activities that could lead to security breaches. The technology can then mobilize a response to neutralize the threat. NLP works seamlessly with Extended Detection and Response (XDR) systems to recognize behavioral indicators of threats, translating these into language patterns for future monitoring.
Real-Time Threat Intelligence With Predictive Analytics
AI is capable of predictive analytics, which is especially useful when coupled with dark web monitoring. When the AI becomes aware of potential threats while analyzing sites and information on the dark web, it can use real-time information to determine if a threat is building, and thereby launch a proactive security measure.
From a security perspective, being able to respond to potential threats proactively offers numerous benefits. These include:
- Quick neutralization of the cybersecurity threat
- Ability to deploy extra security measures against the potential threat’s attack vector
- Increase security in response to the potential threat’s breached access.
This ability to respond proactively instead of reactively saves valuable time in securing your digital platforms.
Intelligent Visualization Tools For Insights
AI-driven tools not only facilitate threat detection on the dark web but also enhance data presentation. Clear, intuitive data visualizations enable cybersecurity teams to make well-informed decisions swiftly, which is crucial given that time is of the essence in cybersecurity operations.
How Zero Fox Utilities AI In Dark Web Monitoring
Zero Fox integrates AI technologies into the security processes that benefit from its tireless and accurate functions. In dark web monitoring, this includes the crawling of sites and pages only accessible through the dark web, and the identification of language and behavior patterns that indicate a threat.
However, it’s essential to understand that while AI provides robust assistance in these tasks, it doesn’t replace the need for human intelligence. Human analysts play a pivotal role in fine-tuning and refining AI systems, ensuring their continual improvement and adapting to evolving threats.
Our dark web threat response also includes our trained Dark Ops team which is familiar with navigating the threats that originate on the dark web.
For a deeper understanding of the symbiotic relationship between AI and human expertise in cybersecurity, refer to our blogs:
- What AI Can and Cannot Offload for Security Teams
- Artificial Intelligence Can’t Yet Replace Intelligence Analysts
Want to learn more about ZeroFox dark web monitoring and how we proactively protect your organization’s information from cyber threats on the Dark Web? Watch this four-minute overview video.
Tags: Deep & Dark Web